DocumentCode
2669388
Title
Examination of the fuzzy subsethood theorem for data fusion
Author
Buede, Dennis M.
Author_Institution
Dept. of Syst. Eng., George Mason Univ., Fairfax, VA, USA
fYear
1994
fDate
2-5 Oct 1994
Firstpage
430
Lastpage
434
Abstract
There continues to be substantial disagreement about which of the several methods to use in measuring and updating uncertainty in data fusion applications. In this paper we examine two popular methods, fuzzy sets and probability theory. Probability theory has been the traditional method for data fusion applications. Fuzzy sets have grown in popularity in Japan and Europe, with many successful control applications. Here we give a simple overview of fuzzy sets and then describe the fuzzy subsethood theorem as the best fuzzy approach for data fusion. Finally we compare the subsethood theorem to Bayes theorem for data fusion applications
Keywords
fuzzy set theory; sensor fusion; uncertainty handling; Bayes theorem; data fusion; fuzzy measures; fuzzy set theory; fuzzy subsethood theorem; probability; target identification; Communication system control; Control systems; Equations; Europe; Fuzzy sets; Intelligent control; Intelligent systems; Measurement uncertainty; Set theory; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Multisensor Fusion and Integration for Intelligent Systems, 1994. IEEE International Conference on MFI '94.
Conference_Location
Las Vegas, NV
Print_ISBN
0-7803-2072-7
Type
conf
DOI
10.1109/MFI.1994.398422
Filename
398422
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